Data Engineer

Cadence ABA builds AI-native clinical data software for ABA therapy, using voice capture and coordinated agents to structure session data, track mastery, and draft billable session notes so clinicians can stay present with the client instead of the tablet. We're looking for a Data Engineer to help build and scale the data infrastructure that powers this clinical platform - from ingesting and structuring trial-level session data to supporting the pipelines behind mastery tracking, graphing, and note generation.

What you'll do

• Design, build, and maintain data pipelines that ingest, transform, and structure clinical session data at scale
• Build and optimize data models and schemas to support analytics, reporting, and downstream product features
• Partner with product and engineering teams to ensure data powering agentic features (mastery tracking, phase-change detection, note drafting) is accurate, timely, and well-structured
• Implement data quality checks, monitoring, and alerting to catch pipeline failures or data anomalies early
• Ensure data handling practices meet HIPAA compliance and support audit-defensible lineage from captured trial to signed note
• Collaborate with backend engineers to design efficient, secure data storage and retrieval systems

What we're looking for

• Experience building and maintaining production data pipelines (batch and/or streaming)
• Strong SQL skills and experience with data modeling for analytical and operational use cases
• Proficiency in a general-purpose programming language commonly used for data engineering (e.g., Python, Scala, or Java)
• Experience with cloud data platforms and orchestration tools (e.g., Airflow, dbt, or similar)
• Understanding of data privacy and security best practices, ideally in a regulated or healthcare-adjacent environment
• Ability to work cross-functionally with product and engineering teams to translate requirements into reliable data systems

Nice to have

• Experience with healthcare data standards or HIPAA-regulated systems
• Familiarity with event-driven architectures or real-time data processing
• Experience supporting audit logging or data lineage systems